Uploaded September 2021 | Updated September 2026, 2 weeks ago

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Writing clean, maintainable code is hard. Writing clean, maintainable Machine Learning code is harder.

While consulting on numerous AI audio/music projects, I noticed that data scientists generally do a pretty good job in R&D, but then struggle to convert scrappy code into well-written ready-for-production code.

To address this issue, I’m publishing a new series called “Uncle Bob’ SOLID Principles for Machine Learning Engineers”.

In this series, you can learn how to use fundamental clean code principles introduced by the legendary software engineer Uncle Bob (SOLID), in order to design your ML code.

Adhering to SOLID principles, will make your ML pipelines easy to understand, flexible, and maintainable.

In the first video of the series, I provide an overview of the course and introduce the SOLID principles.

Slides:
github.com/musikalkemist/solidforml/tree/main/solidforml/01%20Course%20overview

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valeriovelardo.com

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Content:
0:00 Intro
0:29 ML project phases
1:54 The cost of bad code
4:27 SOLID principles at a glance
4:58 Advantages of writing SOLID ML pipelines
5:29 What you'll learn
6:20 How you'll learn
6:47 Who's this series for?
7:32 Prerequisites
7:52 Where do I get slides/code?
8:14 Join The Sound of AI community!
9:02 What's next?